Static analysis

Static analysis, static projection, and static scoring are terms for simplified analysis wherein the effect of an immediate change to a system is calculated without respect to the longer term response of the system to that change. Such analysis typically produces poor correlation to empirical results.[citation needed]

Its opposite, dynamic analysis or dynamic scoring, is an attempt to take into account how the system is likely to respond to the change. One common use of these terms is budget policy in the United States,[1] although it also occurs in many other statistical disputes.

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The term was used in 1977 in an international academic journal,[2] in a discussion of tax policy. In recent years, it has become very common in academic, business, and political discussions of US government economic policy.

A famous example of static analysis comes from overpopulation theory. Starting with Thomas Malthus at the end of the 18th century, various commentators have projected some short-term population growth trend for years into the future, resulting in the prediction that there would be disastrous overpopulation within a generation or two. Malthus himself essentially claimed that British society would collapse under the weight of overpopulation by 1850, while during the 1960s the book The Population Bomb made similar dire predictions for the US by the 1980s.

Similarly, some scientists used a short-term trend of temperature declines during the 1930s to theorize that the world would be in an ice age by 1978. As with the overpopulation theories, the projection was less accurate than a roll of the dice because it didn't take into account how factors interact, nor how a short-term trend was being treated like a long-term trend.

For economic policy discussions, predictions that assume no significant change of behavior in response to change in incentives are often termed static projection (and in the US Congressional Budget Office, "static scoring"). By contrast, dynamic scoring refers to projections based on historical response of population to the effect of economic policy changes such as tax increases or cuts.

Typically, static analysis works for very simple systems: for example, how fast snow is accumulating in what is thought to be the midpoint of a blizzard. But even then it must be tempered with rationality—guess how much longer the storm might actually last, rather than assuming that snow will fall continually for the next sixty years, and project the average of the storm so far, rather than plotting the curve of its growth as if that will continue to increase for the second half.

However, when applied to dynamically responsive systems, static analysis tends to produce results that are not only incorrect but opposite in direction to what was predicted, as shown in the following applications.

A satire on this idea has been presented using the development of safety razors: After their invention, all safety razors were single-bladed for 70 years. Then the first double-bladed razor was introduced. It only required 15 years for a third blade to be added, and then one year for the fourth and fifth. Fitting these five data points to a hyperbolic curve produced the prediction that within nine years of the calculation—by the year 2015—safety razors would have an infinite number of blades.[3]